Back in 2017, The Economist boldly declared that “The world’s most valuable resource is no longer oil, but data.” As we head into 2020, no one would bat an eyelid at this statement. Big data is now used to address an increasing variety of business problems, from product launches to fraud and compliance.
As retail contact center leaders gear up for the busiest time of the year, big data may be the last thing on their minds. However, effective use of customer data offers a significant competitive advantage. This data, gleaned from social media, web visits, call logs, and other sources, can help you improve customer experience (CX) and maximize the value delivered. For example, retailers can provide personalized offers, reduce customer churn, and handle issues proactively.
Achieving this data-centric approach to CX may sound quixotic. However, the reality is that big data is working in the retail industry, and gleaning insights from how other brands have already put it into practice can start you on your own big data journey.
Make it Personal
More than 85% of marketers report success with personalization – higher engagement revenue, conversions. The lesson for customer service leaders?
Recognizing your customer’s interests and preferences – and providing them a singular user experience – is incredibly powerful. Research by Segment found that lack of personalization caused frustration in 71% of consumers and that 44% of them indicated loyalty after personalized shopping.
One manner in which retailers are leveraging customer data is by anticipating their customer’s needs. Using purchase and demographic data, customer service teams can flag common problems with products and expect that a few days after the delivery, consumers may have questions. For example, a company selling a smartwatch may anticipate that some customers may struggle to connect the watch to their phones. A well-timed e-mail to these customers with a set-up guide could lower product returns, and time-consuming customer calls considerably.
Most customer service calls include a disclaimer at the start that the call will be, “Recorded for training and quality purposes.” Big data analysis can bring top issues from these recorded calls to light, and then measure the success of company-led quality changes over time. In one case, speech analytics identified that “true-to-size” information was not communicated about all clothing items in a variety of retail channels. Working with the various stakeholders, they were able to provide better sizing information. This increased online purchases without the assistance of a sales or service professional.
Staffing call centers is a huge challenge for the industry. This challenge is especially apt for retail call centers. For example, Radial, which provides eCommerce services for large retailers, hired 20,000 seasonal employees for its call center, and freight fulfillment centers. One company estimated that it requires two hours of HR staff time to find and hire a single employee. If you need hundreds of agents for your holiday season, that means the process you could take months.
Automated application processes that lean heavily on big data can shave hundreds of hours off the hiring process. Applicants are put through an automated process, which includes recording their voice and giving them simulated calls to answer. The company then crunches the information to decide who should get an interview.
Big data may sound like another buzzword. The reality is that the buzz has dissipated as the applications of big data become commonplace. As technologies continue to advance, we’ll see more improvements to retail call centers and customer service in general, perhaps making the experience of inadequate service a thing of the past.